I was on the 10 o’clock evening news last night on NBC15 Madison to talk about the odds of three people in Dane County winning the Supercash! lottery. There are about half a million residents, and I have no idea how many people play the lottery every day, but I was able to do a few quick back of the envelope calculations
- If everyone in Dane County plays the lottery every day (unrealistic!) then we would expect 3+ people to win in a single day to happen every 0.71 years.
- If half of everyone in Dane County plays the lottery every day (almost all the adults, still unrealistic!) then we would expect 3+ people to win in a single day to happen every 5.12 years.
- If 1 in 10 people in Dane County play the lottery every day (in the ballpark of reality) then we would expect 3+ people to win in a single day to happen every 584 years.
- If 1 in 20 people in Dane County play the lottery every day (in the ballpark of reality) then we would expect 3+ people to win in a single day to happen every 4620 years.
I am having trouble embedding the video, but you can go here to see it.
Area nerd explains the probability of winning the lottery, compares the likelihood of winning the lottery to being eaten by a bear.
Tips for working with the media:
- You can overthink it. “Make things as simple as possible, but not simpler.” Except in this case, even simpler is good. You don’t have a couple of minutes to break apart a concept. Insightful comments that can fit in a tweet are good.
- News moves fast. I was recorded 2 hours after getting the call for the story. In that two hours, I had to take care of things at work, pick up my daughters, and go home. There was very little time for research.
- Crunch some numbers ahead of time to put things into perspective. You may only have time for back of the envelope calculations. If you don’t have all the information (like how many people play the lottery every day), make an assumption and test a few values.
- I find it helpful to explain probabilities in terms of odds (1 in 1.6 million) and expected time to observe the event (every 584 years).
- If you’re dealing with rare events, be prepared to compare the rare event to other rare events. Someone will definitely ask about the odds of getting struck by lightning.
Former INFORMS President Anne Robinson recently talked about operations research and analytics in a YouTube video. As President of INFORMS, she did a lot of work to promote analytics in the OR/MS community and to understand perceptions of analytics vs. operations research. I really appreciate what Anne has done for our field. Her research efforts found that people perceived operations research is a toolbox whereas analytics was perceived as an end-to-end process for data discovery, problem formulation, implementation, execution, and value delivery. This is an interesting finding.
This is Anne’s answer to the question: What is the role of OR in analytics?
“Operations research is on the top of the food chain when it comes to analytic capabilities and potential game changing results.”
I love this.
Anne’s challenge is for us to make decision-makers understand that OR is as vital and necessary as analytics. Evangelize early and often. Given the popularity of analytics, we should be able to make some inroads in educating our peers in STEM about OR, but in the long run this may be tough to do. Analytics is the new kid on the block, and it already seems to have reached widespread adoption, whereas operations research–while being at the top of the food chain–is still somewhat of a mystery to those outside of our fairly small field. Operations research has had an identity crisis for a long time, and I don’t see that coming to an end.
I applaud INFORMS decisions to “own” analytics via Analytics Certification and the Conference on Business Analytics (formerly the INFORMS Practice Conference) rather than try to solely market “operations research” to the growing analytics crowd.
What do you think?
One of the podcasts I regularly listen to (“Stuff Mom Never Told you“) recently has a series of four podcasts on women in STEM (one each for the S, T, E, and M). The engineering and math podcasts were the most interesting. Both podcasts covered many topics, so I’ll just highlight a couple of the topics discussed here.
The math podcast [Link] covered the history of women in math and focused on gender differences in math achievement (and sometimes, the lack thereof).
The engineering podcast [Link] covered pipeline issues in engineering (recruiting and retaining women). They discussed the success of industrial engineering in attracting women. This podcast will be of particular interest to readers of this blog. High school students (both girls and boys) are often unaware of what engineering is, and as a result, students who are good at math choose majors like math and physics instead of engineering. Increasingly, medicine and forensic science are attractive career options to high school students thanks to television programming. This podcast will resonate with those of us in operations research, which is even less known as a field than engineering (Many know that engineering exists, few know what engineers do. Fewer know that operations research exists(!) ).
Here are a few of my posts about women in math, science, and computing:
Miss baseball? Love operations research and analytics? Watch Eric Bickel’s 46-minute webinar called “Play Ball! Decision Quality and Baseball Strategy” here:
Last week I blogged about the husband and wife team that created Major League Baseball schedules for more than two decades [Link]. I discovered another operations research collaboration between a husband and wife team.
Math professor Sommer Gentry and her surgeon husband Dorry Segev discuss how to match kidney donors with those in need of a transplant using networks and integer programming. Their collaboration is featured in the documentary “The Right Match” (below).
In the documentary, they mention how administrators in a single hospital could match up the pairs locally, where there were just a few patients. Integer programming models were needed when considering patients across multiple hospitals, where there are hundreds of patients in need of a transplant. Jump ahead to about seven minutes in to see their discussion of the the network structure of the problem and its similarity to max cardinality matching.
This is a nice video that would be suitable to undergraduate and graduate students studying optimizations. It might be particularly motivating for undergraduates who have learned about less useful applications like the diet problem and optimal mix problems in a linear programming course.
Watch the video here:
Visit their web site: http://www.optimizedmatch.com/
See some of the press their research has received here.
For more reading, I recommend reading more about it on Hari Balasubramanian’s blog here.
Grantland and ESPN has a short video [12:25] on the couple who created the major league baseball schedules in the pre-Mike Trick era (1982-2004). The husband-and-wife team of Henry and Holly Stephenson used scheduling algorithms to set about 80% of the schedule. They found that the their algorithm could not come up with the entire schedule because the list of scheduling requirements led to infeasibility:
“It couldn’t do the whole schedule. That was where the big companies were falling apart. We analyzed the old schedules and found that none of them met the written requirements that the league gave to us. It turns out it was impossible to meet all of the requirements. So the secret was to really know how to break the rules.”
Watch the video here. The end of the video acknowledges how scheduling has evolved such that the entire schedules can be computer generated using combinatorial optimization software (the Stephensons even mention having to compete with a scheduling team from CMU). The video uses baseball scheduling as an avenue to illustrate how decision making and optimization has evolved in the past 30 years. I would highly recommend the video to operations research and optimization students.
Yesterday, Matt Saltzman, Mary Beth Kurz, and Doug Shier were on Clemson University’s radio program “Your Day.” It is an excellent and fun discussion about operations research. The program was archived and is available here:
Here is the program abstract:
Peter Kent is joined by Mary Beth Kurz, Associate Professor in Industrial Engineering, Matthew Saltzman, Associate Professor in Mathematical Sciences, and Doug Shier, Professor of Mathematical Sciences and Associate Dean in the School of Engineering and Science, all from Clemson University. The discussion will focus on the practical application of quantitative methods in rational decision making to solve a wide range of problems arising in business and government, such as locating industrial plants, allocating emergency facilities, planning capital investments, designing communication systems, and scheduling production in factories
The show’s host discovered operations research through the Car Talk Puzzle TSP challenge (Mike Trick blogged about this challenge). Other OR applications discussed included circuit board manufacturing, finding the optimal number of check out lines to open, and whether single-queue/multiple-server models (e.g., bank tellers. Oh wait, no one does that any more. Let’s go with the DMV or going through customs) are better than multiple queue/multiple servers (e.g., the grocery store).